code: def test_step(self, multithreading):
      num_envs = 5
      env = self._make_batched_py_environment(
          multithreading, num_envs=num_envs
      )
      action_spec = env.action_spec()
      observation_spec = env.observation_spec()
      rng = np.random.RandomState()
      action = np.stack(
          [
              array_spec.sample_bounded_spec(action_spec, rng)
              for _ in range(num_envs)
          ]
      )
      env.reset()
  
      # Take one step and assert observation is batched the right way.
      time_step = env.step(action)
      self.assertEqual(num_envs, time_step.observation.shape[0])
      self.assertAllEqual(
          observation_spec.shape, time_step.observation.shape[1:]
      )
      self.assertEqual(num_envs, action.shape[0])
      self.assertAllEqual(action_spec.shape, action.shape[1:])
  
      # Take another step and assert that observations have the same shape.
      time_step2 = env.step(action)
      self.assertAllEqual(
          time_step.observation.shape, time_step2.observation.shape
      )
      env.close()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.environments import batched_py_environment
  from tf_agents.environments import random_py_environment
  from tf_agents.specs import array_spec
  from tf_agents.trajectories import time_step
label_desc: Use image node_id 8 for calling the BatchedPyEnvironmentTest obj's underlying member method code with example usage: obj.test_step(multithreading) without return types